Title :
Study on cloud resource allocation strategy based on particle swarm ant colony optimization algorithm
Author :
Zhengqiu Yang ; Meiling Liu ; Jiapeng Xiu ; Chen Liu
Author_Institution :
Sch. Of Software Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
fDate :
Oct. 30 2012-Nov. 1 2012
Abstract :
Cloud computing environment for the efficient resources allocation is an important issue in the field of cloud computing. The resources in Cloud computing application platform are distributed widely and with great diversity. User demands of real-time dynamic change are very difficult to predict accurately. The heuristic ant colony algorithm could be used to solve this kind of problems, but the algorithm has slow convergence speed and parameter selection problems. Aiming at this problem, this paper proposes an optimized ant colony algorithm based on particle swarm to solve cloud computing environment resources allocation problem.
Keywords :
ant colony optimisation; cloud computing; heuristic programming; particle swarm optimisation; resource allocation; cloud computing application platform; cloud resource allocation strategy; convergence speed; heuristic ant colony algorithm; parameter selection problems; particle swarm ant colony optimization algorithm; real-time dynamic change; resource allocation problem; Algorithm design and analysis; Ant colony optimization; Cloud computing; Heuristic algorithms; Particle swarm optimization; Prediction algorithms; Resource management; Ant colony optimization algorithm; Cloud resource allocation; Particle swarm optimization algorithm;
Conference_Titel :
Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-1855-6
DOI :
10.1109/CCIS.2012.6664453